Data Science Secrets

Author : Jay Samson
Publisher : Trap Door Publishing
ISBN 13 :
Total Pages : 155 pages
Book Rating : 4./5 ( download)

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Download or read book Data Science Secrets written by Jay Samson and published by Trap Door Publishing. This book was released on 2019-09-01 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science Secrets is the #1 strategy guide to break into the field of data and get hired as a Data Scientist, Data Analyst, or Data Engineer. This was created by a group of top Data Scientists and Data Hiring Managers in Silicon Valley to share the secrets of landing your dream job. Here's what's included: Top Interview Questions from companies like Google, Facebook, Amazon, Airbnb, and many more, plus detailed sections on how to answer the questions effectively and get hired. The 8 Week Strategy to find your dream job: learn how to get interviews with your top companies, and more importantly- succeed and get an incredible job offer. Online Learning Breakdown: we go deep into the pros and cons of the online learning options to help you find the right platform for youIn-depth explanations of data roles. There are literally hundreds of different roles and job titles in the world of data- how do you know which is right for you? This section will help you understand how to pursue the role that is the best fit for you

Author : John W. Foreman
Publisher : John Wiley & Sons
ISBN 13 : 1118839862
Total Pages : 432 pages
Book Rating : 4.67/5 ( download)

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Download or read book Data Smart written by John W. Foreman and published by John Wiley & Sons. This book was released on 2013-10-31 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

Author : Ron S. Kenett
Publisher : John Wiley & Sons
ISBN 13 : 111957076X
Total Pages : 142 pages
Book Rating : 4.69/5 ( download)

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Download or read book The Real Work of Data Science written by Ron S. Kenett and published by John Wiley & Sons. This book was released on 2019-04-01 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential guide for data scientists and for leaders who must get more from their data science teams The Economist boldly claims that data are now "the world's most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is "the most valuable resource." "These two authors are world-class experts on analytics, data management, and data quality; they've forgotten more about these topics than most of us will ever know. Their book is pragmatic, understandable, and focused on what really counts. If you want to do data science in any capacity, you need to read it." —Thomas H. Davenport, Distinguished Professor, Babson College and Fellow, MIT Initiative on the Digital Economy "I like your book. The chapters address problems that have faced statisticians for generations, updated to reflect today's issues, such as computational Big Data." —Sir David Cox, Warden of Nuffield College and Professor of Statistics, Oxford University "Data science is critical for competitiveness, for good government, for correct decisions. But what is data science? Kenett and Redman give, by far, the best introduction to the subject I have seen anywhere. They address the critical questions of formulating the right problem, collecting the right data, doing the right analyses, making the right decisions, and measuring the actual impact of the decisions. This book should become required reading in statistics and computer science departments, business schools, analytics institutes and, most importantly, by all business managers." —A. Blanton Godfrey, Joseph D. Moore Distinguished University Professor, Wilson College of Textiles, North Carolina State University

Author : Herbert Jones
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781729642399
Total Pages : 128 pages
Book Rating : 4.9X/5 ( download)

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Download or read book Data Science written by Herbert Jones and published by Createspace Independent Publishing Platform. This book was released on 2018-11 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Did you know that the value of data usage has increased job opportunities, but that there are few specialists? These days, everyone is aware of the role that data can play, whether it is an election, business or education. But how can you start working in a wide interdisciplinary field that is occupied with so much hype? This book, Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't, presents you with a step-by-step approach to Data Science as well as secrets only known by the best Data Scientists. It combines analytical engineering, Machine Learning, Big Data, Data Mining, and Statistics in an easy to read and digest method. Data gathered from scientific measurements, customers, IoT sensors, and so on is very important only when one can draw meaning from it. Data Scientists are professionals that help disclose interesting and rewarding challenges of exploring, observing, analyzing, and interpreting data. To do that, they apply special techniques that help them discover the meaning of data. Becoming the best Data Scientist is more than just mastering analytic tools and techniques. The real deal lies in the way you apply your creative ability like expert Data Scientists. This book will help you discover that and get you there. The goal with Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't is to help you expand your skills from being a basic Data Scientist to becoming an expert Data Scientist ready to solve real-world data centric issues. At the end of this book, you will learn how to combine Machine Learning, Data Mining, analytics, and programming, and extract real knowledge from data. As you read, you will discover important statistical techniques and algorithms that are helpful in learning Data Science. When you have finished, you will have a strong foundation to help you explore many other fields related to Data Science. This book will discuss the following topics: What Data Science is What it takes to become an expert in Data Science Best Data Mining techniques to apply in data Data visualization Logistic regression Data engineering Machine Learning Big Data Analytics And much more! Don't waste any time. Grab your copy today and learn quick tips from the best Data scientists!

Author : Alberto A. Martinez
Publisher : University of Pittsburgh Pre
ISBN 13 : 0822944073
Total Pages : 348 pages
Book Rating : 4.72/5 ( download)

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Download or read book Science Secrets written by Alberto A. Martinez and published by University of Pittsburgh Pre. This book was released on 2011-05-29 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Accessibly written in an engaging style, this book examines classic popular stories in the history of science. Some of the myths discussed include Franklin's Kite, Newton's Apple, and Thomson's plum pudding model of the atom. Martn̕ez successfully holds readers' attention by relying on rich documentation from primary sources to debunk speculations that have become reified over time. He argues that although scientists have disagreed with one another, the disagreements have been productive. Features includes extensive primary source documentation and detailed explanations of how to compare contradictory sources in order to determine which accounts are truly valid"-- Provided by publisher.

Author : Jay Cordes
Publisher : Oxford University Press, USA
ISBN 13 : 0198844395
Total Pages : 263 pages
Book Rating : 4.96/5 ( download)

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Download or read book The 9 Pitfalls of Data Science written by Jay Cordes and published by Oxford University Press, USA. This book was released on 2019-07-08 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science has never had more influence on the world. Large companies are now seeing the benefit of employing data scientists to interpret the vast amounts of data that now exists. However, the field is so new and is evolving so rapidly that the analysis produced can be haphazard at best. The 9 Pitfalls of Data Science shows us real-world examples of what can go wrong. Written to be an entertaining read, this invaluable guide investigates the all too common mistakes of data scientists - who can be plagued by lazy thinking, whims, hunches, and prejudices - and indicates how they have been at the root of many disasters, including the Great Recession. Gary Smith and Jay Cordes emphasise how scientific rigor and critical thinking skills are indispensable in this age of Big Data, as machines often find meaningless patterns that can lead to dangerous false conclusions. The 9 Pitfalls of Data Science is loaded with entertaining tales of both successful and misguided approaches to interpreting data, both grand successes and epic failures. These cautionary tales will not only help data scientists be more effective, but also help the public distinguish between good and bad data science.

Author : Jay Samson
Publisher : Independently Published
ISBN 13 : 9781694746306
Total Pages : 189 pages
Book Rating : 4.05/5 ( download)

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Download or read book Data Science Secrets: How to Get Your Dream Job in Data written by Jay Samson and published by Independently Published. This book was released on 2019-08-12 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science Secrets is the #1 strategy guide to break into the field of data and get hired as a Data Scientist, Data Analyst, or Data Engineer. This was created by a group of top Data Scientists and Data Hiring Managers in Silicon Valley to share the secrets of landing your dream job.Here's what's included: Top Interview Questions from companies like Google, Facebook, Amazon, Airbnb, and many more, plus detailed sections on how to answer the questions effectively and get hired.The 8 Week Strategy to find your dream job: learn how to get interviews with your top companies, and more importantly- succeed and get an incredible job offer.Online Learning Breakdown: we go deep into the pros and cons of the online learning options to help you find the right platform for youIn-depth explanations of data roles. There are literally hundreds of different roles and job titles in the world of data- how do you know which is right for you? This section will help you understand how to pursue the role that is the best fit for you.And much more! Check out our testimonials: "This book made a huge difference in my job search. I was frustrated and unsuccessful for months, but everything changed when I applied the principles in the book. Now I'm making over $120,000/yr and I love what I do" -Aaron P"This book is like a having a personal career coach 24/7. I went from an OK job as a marketing coordinator to a much better (and much better paying) role as a product Data Scientist at a top tech company. 'Data Science Secrets' is worth its weight in gold"

Author : Mohamed Sabri
Publisher : BPB Publications
ISBN 13 : 9390684978
Total Pages : 418 pages
Book Rating : 4.77/5 ( download)

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Download or read book Data Scientist Pocket Guide written by Mohamed Sabri and published by BPB Publications. This book was released on 2021-06-24 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover one of the most complete dictionaries in data science. KEY FEATURES ● Simplified understanding of complex concepts, terms, terminologies, and techniques. ● Combined glossary of machine learning, mathematics, and statistics. ● Chronologically arranged A-Z keywords with brief description. DESCRIPTION This pocket guide is a must for all data professionals in their day-to-day work processes. This book brings a comprehensive pack of glossaries of machine learning, deep learning, mathematics, and statistics. The extensive list of glossaries comprises concepts, processes, algorithms, data structures, techniques, and many more. Each of these terms is explained in the simplest words possible. This pocket guide will help you to stay up to date of the most essential terms and references used in the process of data analysis and machine learning. WHAT YOU WILL LEARN ● Get absolute clarity on every concept, process, and algorithm used in the process of data science operations. ● Keep yourself technically strong and sound-minded during data science meetings. ● Strengthen your knowledge in the field of Big data and business intelligence. WHO THIS BOOK IS FOR This book is for data professionals, data scientists, students, or those who are new to the field who wish to stay on top of industry jargon and terminologies used in the field of data science. TABLE OF CONTENTS 1. Chapter one: A 2. Chapter two: B 3. Chapter three: C 4. Chapter four: D 5. Chapter five: E 6. Chapter six: F 7. Chapter seven: G 8. Chapter eight: H 9. Chapter nine: I 10. Chapter ten: J 11. Chapter 11: K 12. Chapter 12: L 13. Chapter 13: M 14. Chapter 14: N 15. Chapter 15: O 16. Chapter 16: P 17. Chapter 17: Q 18. Chapter 18: R 19. Chapter 19 : S 20. Chapter 20 : T 21. Chapter 21 : U 22. Chapter 22 : V 23. Chapter 23: W 24. Chapter 24: X 25. Chapter 25: Y 26. Chapter 26 : Z

Author : Lillian Pierson
Publisher : John Wiley & Sons
ISBN 13 : 1119811619
Total Pages : 436 pages
Book Rating : 4.19/5 ( download)

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Download or read book Data Science For Dummies written by Lillian Pierson and published by John Wiley & Sons. This book was released on 2021-08-20 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monetize your company’s data and data science expertise without spending a fortune on hiring independent strategy consultants to help What if there was one simple, clear process for ensuring that all your company’s data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that’s most prime for achieving profitability while also moving your company closer to its business vision? There is. Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework – A simple, proven process for leading profit-forming data science projects. Not sure what data science is yet? Don’t worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you’re already a data science expert? Then you really won’t want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book. Data Science For Dummies demonstrates: The only process you’ll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one’s talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise Whether you’re new to the data science field or already a decade in, you’re sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company’s data by picking up your copy today.

Author : Greg Foss
Publisher : O'Reilly Media
ISBN 13 : 1492046418
Total Pages : 333 pages
Book Rating : 4.17/5 ( download)

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Download or read book Practical Data Science with SAP written by Greg Foss and published by O'Reilly Media. This book was released on 2019-09-18 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system. With this practical guide, SAP veterans Greg Foss and Paul Modderman demonstrate how to use several data analysis tools to solve interesting problems with your SAP data. Data engineers and scientists will explore ways to add SAP data to their analysis processes, while SAP business analysts will learn practical methods for answering questions about the business. By focusing on grounded explanations of both SAP processes and data science tools, this book gives data scientists and business analysts powerful methods for discovering deep data truths. You'll explore: Examples of how data analysis can help you solve several SAP challenges Natural language processing for unlocking the secrets in text Data science techniques for data clustering and segmentation Methods for detecting anomalies in your SAP data Data visualization techniques for making your data come to life